在Pyspark中，可以使用filter()函数根据条件将DataFrame拆分为多个DataFrame。以下是一个示例代码：

from pyspark.sql import SparkSession

# 创建SparkSession
spark = SparkSession.builder.getOrCreate()

# 创建示例DataFrame
data = [("Alice", 25, "Female"),
        ("Bob", 30, "Male"),
        ("Charlie", 35, "Male"),
        ("David", 40, "Male"),
        ("Eve", 45, "Female")]

df = spark.createDataFrame(data, ["Name", "Age", "Gender"])

# 按条件将DataFrame拆分为多个DataFrame
male_df = df.filter(df.Gender == "Male")
female_df = df.filter(df.Gender == "Female")

# 打印结果
print("Male DataFrame:")
male_df.show()

print("Female DataFrame:")
female_df.show()

输出结果：

Male DataFrame:
+-------+---+------+
|   Name|Age|Gender|
+-------+---+------+
|    Bob| 30|  Male|
|Charlie| 35|  Male|
|  David| 40|  Male|
+-------+---+------+

Female DataFrame:
+-----+---+------+
| Name|Age|Gender|
+-----+---+------+
|Alice| 25|Female|
|  Eve| 45|Female|
+-----+---+------+

在上述代码中，我们首先创建了一个示例DataFrame，并使用filter()函数将其拆分为两个DataFrame，分别是male_df和female_df。我们通过指定条件df.Gender == "Male"和df.Gender == "Female"来进行拆分。最后，我们使用show()函数打印了两个DataFrame的内容。